197 computer-"https:"-"https:"-"https:"-"https:"-"University-of-St"-"St" positions in Switzerland
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of Medical Microbiology at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast
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at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast data analysis. In
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100%, Zurich, fixed-term The Computational Design Lab is an interdisciplinary research group at ETH Zurich, led by Prof. Dr. Bernd Bickel . We develop novel algorithms and next-generation
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to inform model adaptation and performance evaluation. Implementing ROM methodologies for fluid–structure interaction in wind turbine systems, balancing accuracy and computational efficiency. Validating
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scripting, high performance computing, or advanced statistics and data analysis frameworks (python, R) Regardless of background, the successful applicants will have an interactive personality, motivation
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operating and advancing the data platform, assist interdisciplinary projects that integrate multiple data sources, and use high-performance computing resources to manage and process large environmental
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evaluate prototypes together with industrial partners Profile Required experience CH/EU/EFTA citizenship or valid Swiss work permit PhD in Engineering, Computer Science, Robotics, or related field Strong
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Graduate Institute of International and Development Studies, Geneva; | Switzerland | about 1 month ago
the Department of International Law. They will also be called upon to teach classes and supervise master’s dissertations in the interdisciplinary programme and may be asked to contribute to executive education
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100%, Zurich, fixed-term Human–Computer Interaction in Architecture and Digital Fabrication This fully funded, full-time PhD position spans four years and is embedded within the interdisciplinary
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. Neuromorphic computing and ML deployment on digital and neuromorphic processors TinyML and EdgeAI and ultra-low-power inference for resource-constrained systems Techniques such as quantization, pruning